1. Technical Field
The present disclosure generally relate to image recognition.
2. Description of the Related Art
Image recognition in a digital image, such as recognition of people, characters, or objects existing in the digital image may be widely performed. A template matching technique may be one of recognition techniques for digital images. In the template matching technique, a target object included in an image may be identified (recognized) based on the degree of similarity between a recognition target in the image and an image for reference, referred to as a template image.
In some aspects, the position and direction of the target object in the image may not be fixed. For example, when a character in a landscape image is to be recognized, the shape of the character may be recognized as being geometrically transformed in such a way that the gradient of the character may be recognized as being changed. When the recognition target image is recognized as being geometrically transformed compared to the template image, the appearance of the template image and the appearance of the recognition target image may differ from each other. In such a case, the accuracy of matching may decrease in the template matching technique.
In some aspects, there may be a method for solving this decrease.
A degree-of-similarity calculating device in a related technique may include a displacement vector estimating part, a geometric transformation parameter estimating part, a displacement vector correcting part, a voting part, a peak detecting part, and a degree-of-similarity calculating part. The degree-of-similarity calculating device may operate as described below. In some aspects, the displacement vector estimating part may estimate a displacement vector between a first sub-region set in a first image and a second sub-region most similar to the first sub-region in a second image. The geometric transformation parameter estimating part may estimate a geometric transformation parameter by which the first image is geometrically transformed to the second image, based on multiple displacement vectors. The displacement vector correcting part may subtract displacement based on the geometric transformation from each of the displacement vectors, on the basis of the geometric transformation parameter, and thereby correct the displacement vectors. The voting part may perform voting for the displacement vectors corrected by the displacement vector correcting part in a two-dimensional space determined based on elements of the displacement vectors. The peak detecting part may detect a peak on the two-dimensional space in which the voting is performed. The degree-of-similarity calculating part may calculate the degree of similarity between the first image and the second image based on the magnitude of the peak. The degree-of-similarity calculating device in the related technique may identify (recognize) the target object by using the calculated degree of similarity.
In the degree-of-similarity calculating device in the related technique, it may be assumed that the image quality of the recognition target image is sufficiently high, i.e. the image may have high resolution. Further, in the degree-of-similarity calculating device in the related technique, it may be assumed that the geometric transformation from the template image is the cause of image degradation.
In some aspects, there may be many causes of image degradation, other than the geometric transformation. For example, causes of degradation in recognition of characters in a landscape image may include decrease of resolution of a captured object, generation of blur, and compression noise or sensor noise in an image, in addition to the geometric transformation.
Further, appearance of a template pattern of one class (for example, a certain type of character) in the recognition target image may be sometimes similar to appearance of a template pattern of another class (for example, another type of character) due to the causes of degradation described above. In such a case, the related technique may be difficult to identify the template image corresponding to the recognition target image from the template images.